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A self-taught quantum engineer mapped the synchronization mechanism of biological neural networks to qubits, achieving a 6-qubit GHZ entangled state with 95.11% fidelity and a 14.10% neural synchronization rate on the IBM Quantum Marrakesh quantum computer, providing new ideas for the practical implementation of quantum neural networks.
Section 01
This project, led by Michał Zazuniuk (swiatlowemnie333), maps biological neural network synchronization mechanisms to quantum bits. Key achievements on IBM Quantum Marrakesh include:
The project provides new insights for practical quantum neural network implementations. Source: GitHub repo (released June 2026).
Section 02
Author Michał Zazuniuk has 14 years of industrial automation experience and self-studied quantum computing over the past year. The project explores a core question: Can the synchronization of neurons in biological brains (a basis for collective intelligence) be reproduced using quantum bits?
Section 03
The project first implemented GHZ states on IBM Quantum Marrakesh (156 qubits):
These results were repeated 7 times with high reproducibility. GHZ states exhibit non-locality—measuring one qubit instantly determines all others' states.
Section 04
Building on GHZ entanglement, the team created a quantum synapse model: -6 quantum bits simulating neurons -15 quantum gates as synaptic connections
The model achieved a 14.10% neural synchronization rate. In biology, neural synchronization is key for information integration and consciousness.
Section 05
The project used innovative techniques:
results/ibm_marrakesh_june_2026/ with job IDs like d88n9lgp0eas73dnm190 (GHZ-6) and d88npkqs46sc73f9mt00 (sync experiment).Section 06
The project has multiple implications:
Section 07
Quantum Synapse goes beyond algorithm acceleration—it explores the intersection of quantum physics and biological neural behavior. It’s a bold attempt at bio-inspired quantum neural networks, merging life science and quantum technology to uncover new insights.
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